Persons who inject drugs (PWID) and their risk-related behaviors  have caused severe public health problems, especially in the rapid spread of HIV-1 and HCV. Here, we reconstructed the epidemic history of HIV-1 circulating recombinant form (CRF) 01_AE, CRF07_BC, and HCV subtype-6w among Taiwanese PWID. The timescales were estimated using phylogenetic and Bayesian coalescent analyses. The results revealed that CRF01_AE started to circulate in the Taiwanese PWID population in central Taiwan at 1992.5 (95% credible region: 1988.8–1995.9) and spread to other regions of Taiwan, while CRF07_BC was first identified in southern Taiwan at 2000.0 (95% CR: 1997.8–2002.2) and then spread northward to central-northern Taiwan. All HCV-6 strains were from Asia  and originated in 1928.1 (95% CR: 1890.2–1966.0). Furthermore, subtype-6w isolates from different regions of Taiwan appeared to share a common source that existed in the mid-1990s (95% CR: 1985.0–2001.8) or thereabouts. The routes of drug trafficking and the resulting high prevalence of HIV-1/HCV co-infections among PWID might have contributed to the virus transmission and promoted its spread worldwide. Long-term monitoring and policy implementation in at-risk populations would be useful for disease control. In 2021, 38.4 million people globally were estimated to have lived with HIV and the worst region is still sub-Saharan Africa , MyanmarIn Taiwan, most HIV-1 infected cases in the PWID were CRF07_BC ,11,12. PBoth HIV-1 and HCV are considered blood-borne diseases, which are transmitted mainly through blood contact with infections. The prevalence of chronic hepatitis C in the Taiwanese population is approximately 2.1%, which was among the countries with the higher prevalence in Asia . PaintsiDuring the explosive 2004–2006 outbreak of HIV-1 CRF07_BC among Taiwanese PWID, almost all of them (~99.3%) were HIV-1/HCV co-infections ,11,25. Phttps://www.ncbi.nlm.nih.gov/nucleotide/, accessed on 8 July 2021) in our evolutionary analysis. All Taiwanese PWID were obtained by direct sequencing in our laboratory and those retrieved from GenBank were listed in The research procedures for the current study are shown in Sociodemographic data and information on the types of illegal drugs used, history of drug abuse, risk factors associated with HIV-1 transmission, and years of the first HIV/HCV positive diagnosis were collected using a self-administered questionnaire. Peripheral blood samples were collected to allow analysis of virus genotype. Informed consent was obtained from all participants. Our research protocol was approved by the prisons and detentions administration system, as well as the Institutional Review Board of the National Yang-Ming University, Taiwan. NS5B gene near full-length. Proviral nucleotide sequences were obtained by direct sequencing of PCR products using a DNA analyzer . Viral RNA was extracted from plasma samples using the QIAamp Viral RNA mini kit . Random primer (Promega) was used in reverse transcription to generate cDNA for reverse transcriptase-polymerase chain reaction (RT-PCR). Anti-HCV antibodies from serum samples were detected using an enzyme immunoassay system . Specimens determined with anti-HCV antibodies or confirmed as HIV-1 positive were further analyzed. The genotypes/subtypes of HCV and HIV-1 infections were determined according to the methods described previously ,25,32. Ahttps://www.hiv.lanl.gov/content/index, accessed on 28 May 2021) and the HCV database  was performed using the BioEdit v7.2.6.1 program [env gene, the substitution model GTR + G was incorporated into the ML method, while TN93 + G (GTR and HKY models are not available here) was used to calculate the evolutionary distance for the NJ tree followed by bootstrap analysis with 1000 replicates [NS5B gene, the substitution models for both the ML and NJ tree were K2 + G + I. At least four strains of all subtypes were used as reference sequences and isolates from Asian PWID were included for phylogenetic analysis  and the HCV NS5B sequences (OM287929–OM287937) were obtained from the current study and deposited in GenBank. The HIV-1 Evolutionary rates were obtained using the Bayesian Markov chain Monte Carlo (MCMC) approach implemented in BEAST v2.5.1 . General2 test and Fisher’s exact test were performed in univariate analysis of demographic data. The difference between groups with a p-value < 0.05 was considered statistically significant. The p-values were two-tailed and unadjusted for multiple comparisons. The Pearson χFrom 2004 to 2005, almost all Taiwanese HIV-1 positive PWID were infected with CRF07_BC. However, we found another small-scale outbreak strain that circulated in this population in central-north Taiwan. These were judged according to their time of crime and the place of sentences.n = 24), HIV-1 CRF07_BC (n = 982), and HCV subtype 6w (n = 9) during 2004–2008. The dates of HIV diagnosis and sample collection for most CRF01_AE infections were mainly in 2005 , two were from central Taiwan (Taichung Prison and Yunlin Second Prison), and one was from southern Taiwan (Kaohsiung Prison) .6 constant model to pinpoint the time of the most recent common ancestor (tMRCA) of the HIV-1 strains circulating in this area. Compared to the results of the three models, similar conclusions could be reached  is the best way to present its transmission. Similarly to the estimation of the timescale of HIV-1 spread, we adopted the data set based on GTR + ΓNS5B gene showed that all Asian PWID and reference strains formed a single clade. As summarized in Phylogeny analysis using the gag) [env) and spread to the central-north part of Taiwan in 2002.1  [Takebe et al. reported that CRF07_BC strains from different regions in China  were likely to share a common ancestor that existed in Yunnan province around 1993  ,31. Thisgag) ,31. Furt.9; env) ,13,30, r.9; env) ,12,13,31.9; env) ,13,30,31.9; env) , it onlyThe estimated prevalence of HCV-6 in some regions of Southeast Asia, especially among patients with PWID and major thalassemia, is as high as 50% . InjectiThere are several limitations to this study. First, all Asian isolates  were restricted and obtained from the NCBI website. Second, some Asian isolates were excluded from the evolutionary analysis because the sequences were too short or contained missing sequences. Despite the limitations, this study sheds light on the routes of drug trafficking and the resulting high prevalence of HIV-1/HCV coinfections among PWID that could have contributed to regional and global transmissions. In conclusion, for the first time, we report ‘the time of emergence of common HCV and HIV-1 strains among Taiwanese PWID’ and provide a comprehensive profile suggesting the initial circulation of CRF07_BC in southern Taiwan before spreading to other regions of Taiwan. Furthermore, the importance of using the date of sample collection versus the date of HIV-1 diagnosis was also highlighted when estimating the time of the emergence of the CRF01_AE and CRF07_BC strains. Long-term monitoring and implementation in the population at risk would be useful for disease control.


Moreover, examining the maximal mean power (MPmax) and peak power (PPmax) values (Watts) would allow an understanding of their differences and associations with functionality markers in older adults. Therefore, this research aimed to 1) analyze the load-mean and peak power relationships in the leg press and chest press in older adults, 2) examine the differences between mean Pmax-load (MPmax-load) and peak Pmax-load (PPmax-load) within resistance exercises, 3) identify the differences between resistance exercises in MPmax-load and PPmax-load, and 4) explore the associations between MPmax and PPmax in the leg press and chest press with functional capacity indicators. Thirty-two older adults (79.3 ± 7.3 years) performed the following tests: medicine ball throw (MBT), five-repetition sit-to-stand (STS), 10-m walking (10 W), and a progressive loading test in the leg press and chest press. Quadratic regressions analyzed 1) the load-mean and peak power relationships and identified the MPmax-load, MPmax, PPmax-load, and PPmax in both exercises, 2) the associations between MPmax and PPmax in the chest press with MBT, and 3) the associations between MPmax and PPmax in the leg press with STSpower and 10Wvelocity. In the leg press, the MPmax-load was ∼66% 1RM, and the PPmax-load was ∼62% 1RM, both for women and men (p > 0.05). In the chest press, the MPmax-load was ∼62% 1RM, and the PPmax-load was ∼56% 1RM, both for women and men (p > 0.05). There were differences between MPmax-load and PPmax-load within exercises (p < 0.01) and differences between exercises in MPmax-load and PPmax-load (p < 0.01). The MPmax and PPmax in the chest press explained ∼48% and ∼52% of the MBT-1 kg and MBT-3 kg variance, respectively. In the leg press, the MPmax and PPmax explained ∼59% of STSpower variance; however, both variables could not explain the 10Wvelocity performance (r2 ∼ 0.02). This study shows that the Pmax-load is similar between sexes, is resistance exercise-specific, and varies within exercises depending on the mechanical power variable used in older adults. Furthermore, this research demonstrates the influence of the MBT as an upper-limb power marker in older adults.Identifying the relative loads (%1RM) that maximize power output (P Therefoxercises . For exa–60% 1RM . Interesmachines . Accordimachines . Neverthmax-load for training prescription purposes. For example, regarding this matter, previous research with young trained adults observed that the Pmax-load is exercise-specific and differs according to the mechanical power variable measured (max-load using the mean power (MPmax-load) and peak power (PPmax-load) values in lower and upper-limb resistance exercises in older people. Therefore, to improve the design of resistance training interventions, future research with older people must model the load-mean and peak power relationships in resistance exercises and examine eventual differences between MPmax-load and PPmax-load in the same exercise and the differences in MPmax-load and PPmax-load between resistance exercises.Most studies with older people that modeled the load-power relationship in resistance exercises have primarily prioritized the analysis of the peak power variable . Howevermeasured . These dmax) and peak power (PPmax) values  with markers of functional capacity in older people. For example, several authors observed that the PPmax in the leg press and knee extension could explain 38% of the variance in the short physical performance battery test  in mobility-limited older adults aged 65 years or over  and 3 kg (r = 0.61)  . Neverthmax-load and PPmax-load within resistance exercises, 3) identify the differences between resistance exercises in MPmax-load and PPmax-load, and 4) explore the associations between MPmax and PPmax in the leg press and chest press with functional capacity indicators. We hypothesized that the Pmax-load in the leg press and chest press would be similar between older women and men  analyze the load-mean and peak power relationships in the leg press and chest press in older women and men, 2) examine the differences between MP and men . In addixercises . FinallyIn this cross-sectional study, the participants went to a fitness health club for three consecutive weeks to perform two weekly sessions, separated by 48 h of rest. We dedicated the first 2 weeks to familiarization and anthropometric measures. During this period, we emphasized the proper execution technique of each exercise and movement velocity. Afterward, in the first session of the third week, the participants performed the following tests: MBT with 1 kg (MBT-1 kg) and 3 kg (MBT-3 kg), 10-m walking speed (10W), and five-repetition sit-to-stand (STS). After 48 h of rest, the participants performed a second session constituted by a progressive loading test in the leg press and chest press. An experienced researcher involved in the study and two certified senior fitness coaches supervised the procedures to guarantee safety and proper supervision during each exercise. In addition, verbal encouragement was provided during each exercise to motivate the participants to give a maximal effort. max and PPmax), and an r2 of 0.38 based on the relationship between leg power and the short physical performance battery reported by We estimated a sample size of twenty-three participants to achieve a power of 80%, considering an alpha level of 0.05, two predictor variables  . They pevelocity, in m·s−1) of the best trial.The participants walked 10-m linearly at the maximal intended velocity on an indoor wooden track . They pepower, in W) using a validated equation (The participants stood up and sat down on a chair (0.49 m) with their arms crossed over the chest five times . They peequation , and selIn the leg press , the participants were seated on the bench with their hands on the side handles. They placed their feet on the platform shoulder-width apart, knees at 90°, and back in contact with the seat. In the chest press , the participants were seated on the bench with the handgrips at mid-chest, shoulders abducted, elbows flexed at 90°, and handles grabbed with a full grip. The leg press warm-up consisted of seven repetitions with 20.5 kg plus five repetitions with 29.5 kg, while the chest press warm-up consisted of seven repetitions with 5.7 kg plus five repetitions with 10.2 kg. The initial weight was 29.5 and 10.2 kg in the leg press and chest press, respectively. We increased the weight by 10 kg in the leg press and 5 kg in the chest press until the participants achieved the 1RM. If they could not perform one correct repetition, we decreased the weight by 1–5 kg. The participants performed the repetitions at the maximal intended velocity, and we asked them to perform three repetitions whenever possible to guarantee proper data collection. The inter-set rest was 3 min for three repetitions and 5 min for two repetitions . Using tr), the adjusted coefficient of determination (r2), and the standard error of the estimate (SEE). Quadratic regressions analyzed 1) the load-mean and peak power relationships in the leg press and chest press and identified the MPmax-load (% 1RM), MPmax (W), PPmax-load (% 1RM), and PPmax (W) in the leg press and chest press in women and men, 2) the associations between MPmax and PPmax in the chest press with MBT-1 kg and MBT-3 kg, and 3) the associations between MPmax and PPmax in the leg press with 10Wvelocity and STSpower. We used quadratic regressions to analyze the associations between MPmax and PPmax with functional capacity markers due to the curvilinear relationship between muscle power and functional capacity  the differences between sexes in absolute mean and peak power values (W) in the leg press and chest press for each relative load, including the MPmax-load and PPmax-load, and 2) the differences between sexes in MPmax-load and PPmax-load in the leg press and chest press. A repeated-measures ANOVA with post hoc Bonferroni tests analyzed the differences between MPmax/PPmax in the leg press and chest press with absolute power values (W) at different relative loads in men and women. Paired samples t-test analyzed 1) the differences between MPmax-load and PPmax-load within resistance exercises, and 2) the differences between resistance exercises in MPmax-load and PPmax-load. We performed the statistical analyses in Microsoft Office Excel®  and SPSS v27  and set the significance level at p < 0.05. We designed the figures in GraphPad Prism v7 .We examined the assumption of normality of the data using the Kolmogorov-Smirnov test. We used standard statistical methods to calculate means, standard deviations (SD), 95% confidence intervals (CI), Pearson correlation coefficients (capacity . Indepenmax-load in the leg press did not differ between men and women (p = 0.59). In men, the PPmax was not different from peak power values associated with loads at 60%–65% 1RM (p > 0.05), while in women, the PPmax was not different from peak power values associated with loads at 60%–70% 1RM (p > 0.05) (max-load in the leg press did not differ between men and women (p = 0.62). In men, the MPmax was not different from mean power values associated with loads at 60%–70% 1RM (p > 0.05), while in women, the MPmax was not different from mean power values associated with loads at 65%–70% 1RM (p > 0.05) ( > 0.05) . The MPm > 0.05) .max-load in the chest press did not differ between men and women (p = 0.09). In men, the PPmax was not different from peak power values associated with loads at 40%–65% 1RM (p > 0.05), while in women, the PPmax was not different from peak power values associated with loads at 55%–60% 1RM (p > 0.05) (max-load in the chest press did not differ between men and women (p = 0.41). In men, the MPmax was not different from mean power values associated with loads at 55%–65% 1RM (p > 0.05), while in women, the MPmax was not different from mean power values associated with loads at 55%–60% 1RM (p > 0.05) ( > 0.05) . The MPm > 0.05) .max-load for men and women (p < 0.01). In addition, there were differences between the leg press vs. chest press in MPmax-load for men and women (p < 0.01).max-load vs. MPmax-load in the leg press for men and women (p < 0.01). In addition, there were differences between PPmax-load vs. MPmax-load in the chest press for men and women (p < 0.001).max in the chest press explained 48% of MBT-1 kg variance, while max in the chest press explained 48% of MBT-1 kg variance. In addition, max in the chest press explained 52% of MBT-3 kg variance, while max in the chest press explained 53% of MBT-3 kg variance.max in the leg press explained 61% of STSpower variance, while max in the leg press explained 58% of STSpower variance. In addition, max in the leg press only explained 2% of 10Wvelocity variance, while max in the leg press only explained 1% of 10Wvelocity variance.max-load and PPmax-load within resistance exercises, 3) identify the differences between resistance exercises in MPmax-load and PPmax-load, and 4) explore the associations between MPmax and PPmax in the leg press and chest press with functional capacity indicators. The main findings of the current study were: 1) the MPmax-load and PPmax-load in the leg press and chest press are similar between older women and men, 2) the MPmax-load and PPmax-load differ between resistance exercises, meaning that they are exercise-specific, 3) the Pmax-load varies in the same resistance exercise depending on the mechanical power variable chosen to measure, 4) the MPmax and PPmax in the chest press similarly explain the variability in MBT-1 kg and MBT-3 kg performance, and 5) the MPmax and PPmax in the leg press similarly explain the STSpower variance; however both mechanical variables could not explain the variability in 10Wvelocity performance.The current study aimed to 1) analyze the load-mean and peak power relationships in the leg press and chest press in older women and men, 2) examine the differences between MPmax-load and PPmax-load in the leg press and chest press did not differ between older women and men, which agrees with previous findings, particularly for the peak power values  and chest press (∼40%–65% 1RM) was narrower than those observed for younger populations when using, for example, the squat or bench press exercises (∼30%–70% 1RM)  . These d70% 1RM) . In adding aging . According aging . Therefomax and PPmax in the chest press could similarly explain the MBT-1 kg and MBT-3 kg performance. These data reinforce the influence of the MBT as an indicator of muscle power and functionality in older adults (r = −0.35) in older women  found that hip and ankle muscle strength were better predictors of maximal walking speed than leg strength (As for the regression analysis in the lower limbs, the MPr adults . Howeverr adults . Neverthstrength . Therefostrength . Neverthr2 values observed in our study is in line with previous research (Of note, the range of research , which iresearch . For exaresearch . TherefoThe current study presents several limitations that we need to address. Firstly, a cross-sectional design does not allow us to establish causal relationships between muscle power with functional capacity in the tested population. In this perspective, future longitudinal studies with older adults should examine the effects of resistance training on muscle power and functional capacity and determine their relationships to support causal links. Secondly, although the sample size calculation determined that twenty-three participants were needed to obtain a statistical power of 80%, the actual number of participants is insufficient to generalize the results to other older adults. In addition, considering that our participants were functionally independent, caution should be taken when generalizing these results to mobility-limited older adults. Finally, including physiological and psychological outcomes would be helpful to examine if, along with lower and upper-limb muscle power measures, they could increase the capacity to explain the remaining part of the variance in functional capacity in older adults. Therefore, future research should consider the limitations mentioned above and conduct large-scale, longitudinal, and experimental studies to examine the physiological and psychological mechanisms that better explain the variability in functional capacity in older adults.max-load in the leg press and chest press are similar between older women and men. Nevertheless, the Pmax-load is exercise-specific and varies according to the mechanical power variable chosen for analysis. Therefore, from an applied perspective, this information can be helpful for clinicians, sport-related professionals, and researchers to design experimental interventions oriented to optimizing lower and upper-limb muscle power and functional capacity in older adults. In addition, the current research demonstrated the influence of the MBT exercise as a functional capacity field test for assessing upper-limb muscle power in older adults.This study showed that the P


Understanding temporally attention fluctuations can benefit scientific knowledge and real-life applications. Temporal attention studies have typically used the reaction time (RT), which can be measured only after a target presentation, as an index of attention level. We have proposed the Micro-Pupillary Unrest Index (M-PUI) based on pupillary fluctuation amplitude to estimate RT before the target presentation. However, the kind of temporal attention effects that the M-PUI reflects remains unclear. We examined if the M-PUI shows two types of temporal attention effects initially reported for RTs in the variable foreperiod tasks: the variable foreperiod effect (FP effect) and the sequential effect (SE effect). The FP effect refers to a decrease in the RT due to an increase in the foreperiod of the current trial, whereas the SE effect refers to an increase in the RT in the early part of the foreperiod of the current trial due to an increase in the foreperiod of the previous trial. We used a simple reaction task with the medium-term variable foreperiods (Psychomotor Vigilance Task) and found that the M-PUI primarily reflects the FP effect. Inter-individual analyses showed that the FP effect on the M-PUI, unlike other eye movement indices, is correlated with the FP effect on RT. These results suggest that the M-PUI is a potentially powerful tool for investigating temporal attention fluctuations for a partly unpredictable target. Raising expectations about future behavioral demands, known as “temporal attention” , is ubiquitously employed in a broad range of human behavioral control tasks . TemporaResearchers have investigated temporal attention using the interval periods, i.e., “foreperiods (FPs) ,8.” TypiA significant challenge for previous research on temporal attention in the fixed and variable FP tasks has been the need for a specific response to target presentations because detecting how much temporal attention a participant has developed during the FP before the target presentation is impossible. Estimating the users’ temporal attention during the FP in controlled experiments would be the first step in developing user-friendly systems that analyze users’ temporal attention and developing advanced adaptive interfaces that adjust the information presentation timing by sensing users’ temporal attention.The pupilar diameter can be used to estimate the degree of temporal attention robustly in fixed FP and partially in medium-term variable FP tasks. The muscles that influence the pupilar diameter, which is innervated by the autonomic nervous system, reflect the cortical state of the central nervous system related to temporal attention –34. As sThe current study focused on estimating temporal attention in the medium-term variable FP using the pre-target pupilar index among these four categories. In reality, it is unlikely that users always know the timing of the target presentation. Therefore, estimating temporal attention to partly unpredictable targets  is particularly necessary. To our knowledge, there are no previous pupillometric studies of the short-term variable FP paradigm, although there are studies of the medium-term variable FP paradigm. If we were to develop systems that interact with users based on their temporal attention estimates, it would be desirable to target medium-term temporal attention situations, including driving (excluding urgent reactions) and computer work situations, rather than short-term temporal attention situations such as a sprinter waiting for the sound of a pistol. Also, such estimates must be conducted before presenting the target. Therefore, the estimation must be conducted using the pre-target pupilar index. Several findings suggest that the pre-target pupilar index might reflect temporal attention in fixed FP tasks ,26. The A better index for estimating temporal attention in the medium-term variable FP is the pupillary fluctuation amplitude before target presentation, or the Micro-Pupillary Unrest Index (M-PUI) . We haveThe current study, in contrast, investigated the relationship between the M-PUI and RT differences in different FPs (n/n-1) to examine the possibility that M-PUI reflects the effects of FP and SE on RT cf. . As descFinally, we confirmed that other eye movement indices did not substantially mediate inter-individual correlations between the FP/SE effects on RT and M-PUI. For example, the pupilar diameter measured from a camera placed facing the face varies depending on the gaze position . We examTo test these hypotheses, we used the data we collected in the previous study  because We decided to examine the validity of M-PUI on smoothed pupilar diameter with a 75 ms window during the few seconds before target presentation  using a The Micro-Pupillary Unrest Index (M-PUI) has been proposed as an index of pupillary fluctuation amplitude that can be calculated quickly . As indiThe participants were individuals with normal or corrected-to-normal vision who applied to participate as a part-time job . They were recruited outside the laboratory and received payment for participating in the study. The recruitment process and the experimental procedures were approved by the NTT Communication Science Laboratory Research Ethics Committee (Reference Number H29-004). All the experiments were conducted according to the 1964 Declaration of Helsinki. Written informed consent was obtained from all individuals that participated in the study.Participants sat at a distance of 60 cm from an LCD monitor . Stimuli were presented using Psychopy2 on a black background. The target was a white dot in the center of the screen, shown at a visual angle of 2.9 degrees. Left eye movements were recorded using the SR Research Eyelink 1000 with a sampling rate of 1,000 Hz. We stabilized the participants’ heads with a chinrest during the entire task.The participants conducted eight tasks. We used the data of one of these tasks in the current study. The order of the tasks, which took approximately ten minutes to conduct, was randomized. A ten-minute break followed the tasks. Two participants were paired in the task sessions so that one could take a break while the other performed the task. The total procedure took 180–210 minutes, including the time for preparing the apparatus.The PVT took approximately 10 min. We used the pupilar diameter during the interval of 500 ms after starting the trial to target appearance because the pupilar diameter immediately after the start of a trial could include its fluctuations to the target detection/response in the previous trial . We alsoThe procedure for calculating the M-PUI was adopted from our previous study . FirstlyWe calculated the mean pupilar dilation, standard deviation (SD) of the pupilar diameter, mean eye closure time, the mean number of blinks, mean horizontal , and vertical  distance of the gaze position from the center of the screen, and the SD of the gaze position . Specifically, we calculated the mean pupilar dilation for each trial by subtracting the baseline pupilar diameter at the time of starting the interval  from the pupilar diameter at a specified interval because M-PUI might be correlated with pupilar size (cf. ). The stThe data of 17 participants were valid. We excluded 3 participants due to technical errors such as inconsistent calibration results. We conducted 1,972 trials, to most of which the participants responded correctly without missing any trials. There were only nine false alarm trials with RTs of 150 ms or less. When calculating the RT, we excluded trials with misses and false alarms (including anticipatory responses shorter than 150 ms). In calculating eye movement indices, including the M-PUI, we excluded trials in which the measured eye was not open for an interval of over 500 ms, i.e., over half of the M-PUI calculation interval of 1,000 ms.We first plotted M-PUI and RT of second-to-second FPs (n/n-1) to describe the data generally. The FP (n/n-1) of the 1,500 ms point includes trials with FPs between 1,000 to 1,750 ms, the 2,500 ms point includes FPs between 2,000 to 2,750 ms, the 3,500 ms point includes FPs between 3,000 to 3,750 ms, the 4,500 ms point includes FPs between 4,000 to 4,750 ms, the 5,500 ms point includes FPs between 5,000 to 5,750 ms, the 6,500 ms point includes FPs between 6,000 to 6,750 ms, and the 7,500 ms point includes FPs between 7,000 to 8,000 ms FPs. To mitigate the trial size reduction, we changed the trial exclusion criteria to the criteria that the eye was unopened for over 333 ms, i.e., over one-third of the M-PUI calculation interval of 1,000 ms, presented as preliminary analyses because the number of trials per plot was small.r = 0.77, p < .001). Except for the SD of pupilar diameter , no other eye movement indicators had a significant relationship with RT in terms of FP (n) slopes. The mean number of trials for each plot point was 14.00 (±1.29).Regarding the FP effect, the plot for each FP (n) is shown in r = - 0.11, n.s.). The FP (n-1) slopes showed no other eye movement indicators having a significant relationship with RT except the number of blinks . The mean number of trials for each plot point was 6.24 (±0.87).We examined whether the general pattern of mean M-PUIs for short and long FP (n/n-1), was similar to mean RTs. See t(16) = 4.80, d = 0.59, p < .0001) and the mean M-PUIs for short FP (n) was significantly larger than those for long FP (n), (t(16) = 2.31, d = 0.36, p < .05). The mean numbers of trials for short and long FP (n) were 38.06 (±8.40) and 45.53 (±7.23), separately.The mean RTs/M-PUIs for short FP (n) and long FP (n) are shown in t(16) = 1.77, d = 0.36, p = .05), the average M-PUIs for long FP (n-1) were not significantly larger than those for short FP (n-1), (t(16) = 1.58, d = 0.29, n.s.). The mean numbers of trials for short and long FP (n-1) were 17.65 (±4.43) and 14.53 (±3.99).As shown in Then, we calculated the inter-individual correlation between the individual magnitudes of FP/SE effects for RT and M-PUI; cf. r) and Biweight midcorrelation (bicor), which is an outlier robust, median-based correlation metric [r = 0.73, p<001; bicor = 0.64, p<01).We first calculated the inter-individual correlation between the FP effects on RT and M-PUI; cf. the upper panel of n metric . The scar = 0.39, n.s.; bicor = 0.27, n.s.).We also calculated the inter-individual correlation between the SE effects on RT and M-PUI; cf. the lower panel of r and bicor. Moreover, only the number of blinks was significant for the SE effect, as indicated by r (p < .01) and bicor (p < .05).Finally, we examined the inter-individual correlation between the FP/SE effects on RT and other eye movement indices, including the mean pupilar dilation, standard deviation (SD) of the pupilar diameter, the mean eye closure time, the mean number of blinks, the mean gaze position distance from the center of the screen (in X and Y-axis), and the SD of the gaze position (in X and Y-axis). The inter-individual correlations between the FP/SE effects on RT and eye movement indices are shown in r and bicor again indicated that only the M-PUI reached a strictly corrected significance level of p < .0055 for dividing points of 4,000 to 5,000 ms. Except for the SD of the pupilar diameter, no other eye movement indices showed a significant correlation at a corrected level of p < .0055. The mean numbers of trials for short FP (n) in each condition were 14.35 (±5.49), 20.00 (±6.63), 26.06 (±7.14), 32.00 (±7.58), 38.06 (±8.40), 44.53 (±9.11), 51.00 (±9.89), 57.41 (±11.12), and 64.12 (±11.96). The mean numbers of trials for long FP (n) in each condition were 69.24 (±10.10), 63.59 (±9.03), 57.53 (±8.56), 51.59 (±7.92), 45.53 (±7.23), 39.06 (±6.10), 32.58 (±5.39), 26.18 (±4.18), and 19.47 (±3.01).We conducted supplementary analyses to test further the robustness of the inter-individual positive correlation between FP/SE effects on RT and M-PUI using different dividing points that ranged from 2,500 to 6,500 ms in 500 ms increments  in each condition were 7.41 (±2.09), 9.65 (±2.30), 12.41 (±3.40), 14.94 (±3.95), 17.65 (±4.43), 20.06 (±5.20), 22.59 (±5.78), 24.82 (±6.00), and 26.88 (±6.49). The mean numbers of trials for long FP (n-1) in each condition were 24.76 (±6.01), 22.53 (±5.65), 19.76 (±4.85), 17.23 (±4.25), 14.53 (±3.99), 12.12 (±3.18), 9.59 (±2.68), 7.35 (±2.35), and 5.29 (±1.87).The correlations between the SE effects on RT and all eye movement indices for each dividing point are shown in The current results suggest that the M-PUI dynamically reflects the FP effect in which temporal attention varies according to the current FP of several seconds. We reproduced the FP effect on RT, in which the RT is shorter when the current FP is longer. Similarly, the M-PUI was shorter when the current FP was longer. In addition, the decrease in M-PUI immediately before target presentation, i.e., 1,000 ms (cf. ), with tThe M-PUI may be the first step in estimating temporal attention in realistic, medium-term variable FP situations. The FP effect is only one typical effect observed in the simplest of possible temporal attention situations in which a response to a target is always required after the medium-term variable FPs under the uniform distribution. Nevertheless, none of the pupilar indices used to date can estimate temporal attention during the variable FP, even in this most straightforward situation cf. . One stuThis study also suggested that the M-PUI might not reflect the SE effect that varies according to the previous FP. The current study did reproduce the SE effect for RT by showing that the RT to the target presented in the early part of the current trial was longer if the previous FP were longer. However, the M-PUI was not significantly longer when the previous FP was longer. In addition, the decrease in M-PUI immediately before target presentation, i.e., 1,000 ms (cf. ), when tThe finding that M-PUI might reflect the FP effect but not the SE effect of temporal attention extends our findings on M-PUI. Our previous study found that M-PUI correlated with RT on a within-individual trial-by-trial basis, regardless of the length of current or previous FPs . As a reThe current study might have included different factors that caused inter-individual variability in the FP and SE effects. Medium-term variable FP studies on the FP effect suggest that people conditioned to perform well on the task consistently have shallower FP (n)-RT slopes with generally shorter RTs ,24,37. OThe current study did not control participants’ working memory capacity, sleep schedules, or personality traits, which might have caused individual differences in participants’ temporal attention in the variable FP task. The motivation to perform the task might differ from one individual to another, even though the rewards were not different for different participants. These background factors might affect biological systems controlling temporal attention in the medium-term variable FP task, and the M-PUI could reflect these systems’ conditions. M-PUI’s validity in estimating individual differences is critical because it is essential to account for individual differences in participants’ temporal attention in realistic environments and develop user-friendly systems by estimating temporal attention. One direction for future research is investigating factors causing individual differences in biological mechanisms supporting temporal attention in medium-term variable FP tasks.There are no indices of eye movements during the FP that robustly reflect the FP effect on RT other than the M-PUI. The M-PUI cannot be substituted by the widely used pupilar dilation index . The pupilar diameter’s SD might reflect the FP effect on RT; however, the M-PUI appears to extract signals better. The M-PUI focuses only on short-term fluctuations of pupilar diameter . In contrast, the pupilar diameter’s SD includes all the variability in the pupilar diameter’s time series. These findings suggest that temporal attention involving the FP effect is related to biological systems reflected by pupilar diameter’s short-term fluctuations rather than to the mean pupilar diameter or any other pupilar diameter variability. Also, the effects of short-term pupilar diameter fluctuations cannot be substituted by possible artifacts caused by the eye closure time, the number of eyeblinks, or gaze position variations.We have proposed two possible mechanisms underlying the M-PUI’s reflection of the FP effect after considering the three temporal attention models: the dual-process model ,32–34, tTwo mainstream models explain the FP and SE effects of temporal attention in the short-term variable FP paradigm: the dual-process model (DPM) ,32–34 anThe DPM assumes that top-down and bottom-up processes produce the FP and SE effects ,32–34. TIn addition, the bottom-up process is assumed to cause a trial-by-trial, constant, higher (lower) automatic motoric arousal after a shorter (longer) FP (n-1). However, the top-down effect is assumed to, in some way, overwrite these automatic differences in motoric arousal in longer FP (n). Consequently, RT differs due to FP (n-1) only in shorter FP (n), resulting in the SE effect. Neuropsychological studies have shown a double dissociation in the localization of top-down and bottom up-processes –34. The The MTP assumes that a response is made according to the sequences of the inhibition/activation reaction’s strength based on the memory traces formed up to a given trial ,15. The The MTP explains the FP effect by considering the biased number of memory traces for FP lengths . The nuThe MTP explains the SE effect based on the identical but especially strong mechanism as the FP effect . SpecifRecent studies have supported a modified version of the MTP, where different memory traces have different influences on the FP and SE effects, incorporating the DPM’s physiological suggestions ,46–49. TWe first propose that the reduction of the M-PUI might reflect the degree of LC-NE’s preparation for the phasic enhancement of target detection/reaction that increases as FP (n) increases. As assumed previously , this exBelow, we have summarized the relationship between the contemporary LC-NE excitatory account and previous temporal attention models. It is reasonable to assume that M-PUI reflects the FP but not the SE effect in terms of the DPM and RV, which suggest separate processes in the FP and SE effects. In contrast, it is inconsistent that M-PUI’s selective reflection of the FP in terms of the MTP, which emphasizes long-term  and short-term  memory traces, operates through the identical unidimensional inhibition/activation mechanism . PerhapsOne difficulty with the above scenario of the medium-term variable FP paradigm is a study suggesting that post-target transient pupilar dilation does not increase as the FP (n) lengthens . This stWe also propose that M-PUI might reflect the degree of perceptual/response inhibition representations that rapidly increase when FP (n) is short and decreases gradually when FP (n) gets longer. The inhibitory account considers that participants’ pupilar diameter is stable in the baseline condition but unstable in the inhibited state (cf. ). The inBelow, we have summarized the relationship between the inhibitory account and previous temporal attention models. The DPM does not suggest this account because it does not mention inhibitory mechanisms; however, there is no contradiction between this account and the DPM. The MTP suggests this account because it provides an inhibitory account of the FP and SE effects. However, it is nevertheless inconsistent with the selective reflection of the FP effect by the M-PUI. Similar to the excitatory LC-NE account, we have assumed that physiologically diverse mechanisms separately support the FP and SE effect in the MTP. The RV is highly consistent with this account because M-PUI is related to the top-down, inhibitory FP effect but not to the bottom-up SE effect.For the time being, the above discussion remains a hypothesis worth investigating. Future research is needed to clarify whether the results of the current study can be explained by excitation, inhibition, or both mechanisms. Furthermore, the specific physiological pathways by which M-PUI might capture inhibition-related signals remain unclear. We suggest that it might occur through the interplay cf. ,55,57) b,57 b55,5A possible direction for future research might be to consider the quick dynamic acquisition of the internal probability estimates in the past few trials, which results in executing perceptual inputs and motor outputs in the current trial (cf. ). The coThe findings of the current study are constrained by several limitations. Firstly, the range of variable FPs used in the current study was limited. Many typical variable FP paradigms, which we call the short-term variable FP paradigm see the , have beSecondly, there are other differences between the experimental manipulation of a typical variable FP paradigm and the current task. This study followed the original PVT in investigating the effect of variable FP in the PVT. Consequently, we terminated the target presentation immediately after a response. We also presented RT as feedback. Furthermore, we did not judge a miss until 60 seconds after the target presentation . These eThirdly, the findings of this study are limited because of reusing old data. From the perspective of the experimental manipulation, we verified the current findings only in one specific experimental situation. Therefore, it might be necessary to verify the robustness of the current findings by changing the parameters of the current experimental situation. From the perspective of statistical hypothesis testing, each repeated independent hypothesis test for a given data set leads to an increase in the probability of rejecting the null hypothesis . AlthougThe M-PUI before target presentation reflected the variable foreperiod effect  on RT and even reflected individual differences in the FP effect on RT in the medium-term variable FP paradigm. Also, the M-PUI can be calculated before presenting a target. Therefore, it has the potential as a tool for estimating attentional fluctuations in the applied contexts. We have discussed the possible association between this finding and the phasic activity of the LC and the inhibitory signals as a mechanism underlying this effect.


Type 1 diabetes mellitus (T1DM) is a complex metabolic disease characterized by a massive loss of insulin-producing cells due to an autoimmune reaction. Currently, daily subcutaneous administration of exogenous insulin is the only effective treatment. Therefore, in recent years considerable interest has been given to stem cell therapy and in particular to the use of three-dimensional (3D) cell cultures to better reproduce in vivo conditions. The goal of this study is to provide a reliable cellular model that could be investigated for regenerative medicine applications for the replacement of insulin-producing cells in T1DM. To pursue this aim we create a co-culture spheroid of amniotic epithelial cells (AECs) and Wharton’s jelly mesenchymal stromal cells (WJ-MSCs) in a one-to-one ratio. The resulting co-culture spheroids were analyzed for viability, extracellular matrix production, and hypoxic state in both early- and long-term cultures. Our results suggest that co-culture spheroids are stable in long-term culture and are still viable with a consistent extracellular matrix production evaluated with immunofluorescence staining. These findings suggest that this co-culture may potentially be differentiated into endo-pancreatic cells for regenerative medicine applications in T1DM. Type one diabetes mellitus T1DM) is a complex autoimmune disorder characterized by the immune-mediated destruction of insulin-producing beta cells. This condition leads not only to increased blood glucose levels but also to alterations in the micro and macro blood circulation, which implies an increased risk to develop nephropathy, retinopathy, and neuropathy DM is a c. The difIn our study, we focus on two different perinatal cells: amniotic epithelial cells (AECs), isolated from the inner part of the amniotic membrane, and Wharton’s jelly mesenchymal stromal cells (WJ-MSCs), isolated from the umbilical cord. Due to their early development, perinatal cells retain characteristics found in pluripotent stem cell populations and have been successfully induced to differentiate towards all three germ layers under specific culture conditions . ImportaThanks to the advancements in matrices and scaffold engineering, studies on three-dimensional (3D) cultures have increased in recent years. Spheroid formation is usually achieved through the use of these techniques: (a) forced floating, (b) hanging drop, (c) spinning flask, (d) rotating vessel, (e) electrical-force assisted, (f) magnetic-force assisted, and (g) matrix-based . Three-dAmong 3D models, spheroids are dense cellular structures that are promising to increase the therapeutic potential of cell-based therapies. Specifically, spheroids retain their extracellular matrix (ECM), which is fundamental to increasing cell survival in harsh conditions and up-regulating trophic factor secretion. Thanks to the presence of ECM and cell–cell interactions, spheroids better mimic the micro-environment found in native tissue . MoreoveThis study was approved by the Local Ethical Committee . Placentas were obtained from healthy donor mothers undergoing elective caesarean section at term (37–40 weeks) after written informed consent. Perinatal tissues were maintained under sterile conditions until specific cell isolation was performed.2 approximately) and digested twice for 30 min at 37 °C using trypsin-EDTA 0.25%  with gentle shaking. For both digestion steps, trypsin was inactivated with fetal bovine serum  and the cell suspension was centrifuged for 10 min at 390× g. The cell pellet was resuspended in basal culture medium, Dulbecco’s Modified Eagle’s Medium–high glucose  containing 10% FBS, 1% penicillin-streptomycin solution, and 10 ng/mL of epithelial growth factor . The single-cell suspension was counted and tested for viability using erythrosin B . Only samples with >90% viability were used for further assays.Fetal membranes were washed with ice-cold phosphate-buffered saline  with 1% penicillin–streptomycin solution . The amniotic membrane was mechanically peeled off the underlying chorion layer to remove any blood clots. Then the tissues were incubated for 10 min at room temperature with PBS/ethylenediaminetetraacetic acid (EDTA) 0.5 mM. The amniotic membrane was then minced into small pieces  and centrifuged at 300× g for 5 min. After centrifugation, cells were recovered and the single-cell suspension was counted and tested for viability using erythrosin B .First, the umbilical cord (UC) was removed from the placenta. UC was minced into pieces of approximately 2–3 cm lengths and rinsed 3–4 times with phosphate-buffered saline  containing 1% penicillin–streptomycin . After the removal of two arteries and a vein, Wharton’s jelly (WJ) was chopped into pieces of 3–5 mm with a scalpel. These small pieces were transferred onto the culture dishes and covered with a drop of Dulbecco’s Modified Eagle’s Medium (DMEM) with 10% FBS  to prevent the pieces of WJ from drying out. The dishes were placed in the incubator with 5% COImmunophenotypic characterization of isolated AECs and WJ-MSCs was performed using flow cytometry. Cells were fixed for 10 min at room temperature using Intraprep Kit  and washed twice with PBS. Cells were incubated for 30 min at 4 °C with conjugated primary antibodies (1 μg/mL) specific for epithelial (anti-pan Cytokeratin (Pan-Ck)-PE, Santa Cruz Biotechnology, Santa Cruz, CA, USA), mesenchymal , hematopoietic , and stem cell (anti-state-specific embryonic antigen-4 (SSEA4) APC, Miltenyi Biotech, Germany) markers. For the analysis of Pan-Ck, we used the Pan-Ck Type I/II Antibody Cocktail  and anti-mouse–Alexa Fluor 488  as a secondary antibody. After incubation, cells were washed with PBS and analyzed using the FACS Navio FC  cytometer and the Kaluza FC C 1.2 Analysis software .g for 3 min and placed in an incubator at 37 °C with 5% CO2. The culture media was changed every day thereafter.Spheroids were generated starting from isolated WJ-MSCs seeded as mono-culture or by combining WJ-MSCs with AECs using 96-well round-bottom cell-repellant plates . Briefly, 200 μL of DMEM with 10% FBS containing a total of 5000 cells/well were seeded in each well in both mono- and co-culture spheroids. In the co-culture setting, 2500 cells/well of each cellular subtype and EGF (10 ng/mL) were added. Immediately after seeding, the plates were centrifuged at 50× 6 cells/mL in serum-free DMEM were incubated for 20 min at 37 °C with the corresponding labelling solution (5 μL/mL). Cells were washed twice in PBS and seeded in 96-well round-bottom cell-repellant plates. Immediately after seeding, the plates were centrifuged at 50× g for 3 min and placed in the IncuCyte® S3 live imaging system (Sartorius) for 96 h at 37 °C in 5% CO2. Bright-field and immunofluorescence images were acquired using 10× magnification every 3 h from the seeding to the complete spheroid formation after 96 h.Co-culture spheroids were generated starting from isolated WJ-MSCs stained using Vybrant™ DiD Cell-Labeling Solutions  and AECs stained using Vybrant™ DiO Cell-Labeling Solutions . Biefly, 1 × 10® stock solution was added and incubated for a maximum of 24 h at 37 °C under 5% CO2 humidified conditions. The reduction of the reagent was measured at 595 nm at 2, 4, 6, 8, and 24 h using a multiplate reader . To determine the presence of metabolically active cells in our spheroids the resazurin reduction assay was performed . The assCell viability within the spheroids was tested using the Live/Dead Cell Assay Kit (Life Technologies). This assay was used to visually determine the group of cells within spheroids maintaining viability after clusterization indispensable for spheroid formation. Spheroids of mono- and co-culture at 4 and 14 days were incubated with a solution containing 1 μM calcein AM and 2 μM ethidium homodimer-1 at 37 °C for 45 min. After washing with PBS, spheroids were imaged with laser excitation of the sample at 488 nm and 561 nm using a Nikon Inverted Microscope , and images were acquired with a Digital Sight camera DS-03 using the imaging software NIS-Elements 4.1 .The spheroids were washed in PBS and transferred to 1.5 mL Eppendorf tubes to encapsulate them with Epredia™ HistoGel™ Specimen Processing Gel . Each gel specimen was moved to a cassette and loaded inside a tissue processor . The samples were embedded in paraffin blocks using an automated inclusor . Microtome  sections of 10 µm were placed on Super Frost glass slides  and allowed to dry. The sections were deparaffinized with 2 changes of xylene for 5 min and rehydrated with 2 changes of 100% ethanol, followed by washes in 90% ethanol and 70% ethanol for 3 min. Finally, the slides were rinsed in distilled water.The slides were deparaffinized, rehydrated, and stained with hematoxylin and eosin. The sections were stained with Gill 2 hematoxylin (Bio-Optica) for 5 min, washed in tap water for 3 min, rinsed with distilled water, and subsequently stained with 1% eosin G (Bio-Optica) for 10 min, dehydrated in ethanol of ascending concentration , clarified in pure xylene, and mounted with Bio Mount balm (Bio-Optica). Stained sections were observed using a Leica DM 750 equipped with a Leica ICC50 HD digital camera.The W8 instrument (CellDynamics SRL) is able to accurately measure the size, weight, and density of the spheroids. Single spheroids free-fall into a vertical flow channel dedicated to analyzing their terminal velocity. The physical approach of this analysis and the mathematical equations used for the calculation is extensively described by Cristaldi et al. . Before Antigen retrieval was performed by incubating slides of sectioned spheroids in sodium citrate pH 6 at 95 °C for 30 min. Sections were washed with PBS and permeabilized by adding PBS 0.3% Triton  for 10 min. Slides were incubated for 30 min with a blocking solution containing PBS 4% bovine serum albumin  and 0.3% Triton, then incubated overnight at 4 °C with the primary antibodies anti-vimentin , anti-pan cytokeratin , anti-laminin , anti-fibronectin , anti-cadherin , and anti-collagen I  diluted in blocking solution. Secondary anti-mouse Alexa Fluor 488  and Alexa Fluor 594  were used for 1 h incubation at room temperature. After three washes with PBS, coverslips were mounted using the Prolong Gold Antifade Mountant with DAPI . Stained cells were observed using a Nikon Inverted Microscope , and images were acquired with a Digital Sight camera DS-03 using the imaging software NIS-Elements 4.1 .The hypoxia level of whole-mounted spheroids was evaluated using the hypoxia LOX-1 probe (Organogenix- MBL) according to the manufacturer’s instructions. The probe was added to the culture medium at a final concentration of 2 μM 24 h before detection. Images visualizing the hypoxic area in mono- and co-culture spheroids were obtained using a Nikon Inverted Microscope , and images were acquired with a Digital Sight camera DS-03 using the imaging software NIS-Elements 4.1. The percentage of the hypoxic area within a total spheroid area was determined.t-test using Graph Pad Prism 9.0 software . The significance threshold was set at p < 0.05.All the experiments, except the one for which details were already described, were performed on at least three human samples in technical triplicate. Data are presented as mean ± standard deviation (SD) and were analyzed with two-way ANOVA or The immuno-phenotypic profile of isolated AECs and WJ-MSCs was characterized using a flow cytometry approach. The epithelial, mesenchymal, and hematopoietic markers were evaluated. As shown in To enhance cell–cell interactions, cells were seeded in cell-repellent plates, resulting in the formation of three-dimensional structures  using the IncuCyteSince the majority of the differentiation protocols in endo-pancreatic linages consist of 14 days of culture [® assay, as shown in The viability of cells within the spheroids was evaluated using a Live/Dead Cell Assay Kit. The ethidium homodimer-1 staining indicates a compromised cell membrane (red fluorescence), and calcein fluorescence highlights viable cells (green fluorescence) a. The WJHematoxylin and eosin staining was performed on spheroid sections at the early and late time points for both WJ-MSC mono-culture and co-culture. In We analyzed mono-cultures of WJ-MSCs and co-cultures of WJ-MSCs and AEC spheroids obtained as described above. At least ten single spheroids for each condition were analyzed at four time points: 4, 7, 10, and 14 days of 3D culture. For each spheroid, the diameter and the mass density were analyzed. Experiments were performed on a homogeneous population of spheroids in terms of cell number (5000 cells/spheroid) to evaluate the contribution of each cell population in terms of density and diameter. Mono- and co-culture spheroid samples were fixed with 4% PFA and analyzed with the flow-based system. The diameter of WJ-MSC spheroids (μm), calculated automatically from the images acquired during the analysis, was stable during the four time points, as was the mass density . The aveWe investigated the presence of cadherin molecules in mono- and co-culture spheroids to evaluate cell–cell interactions. Cadherins are fundamental players in spheroid formation as they create homophilic cadherin–cadherin binding that contributes to spheroid compaction ,18. CadhAs the formation of the spheroids occurred through a self-organization process, we wanted to further characterize the structure of our 3D model co-culture to inspect the arrangement of the two cellular components within the spheroid and evaluate possible alterations during the long-term culture. Thanks to the immunofluorescence staining of the epithelial cell marker Pan-Ck , it was We evaluated the presence of ECM proteins in our spheroids. ECM is widely known to provide structural support in tissues and also plays important roles in cell behavior, including cell adhesion, migration, and compartmentalization . In partTo further characterize WJ-MSC mono-culture and co-culture spheroids we evaluated the hypoxic state at 4 and 14 days. A hypoxia LOX-1 probe  was usedCurrently, T1DM therapy is based almost exclusively on the control of insulin levels through the administration of exogenous insulin. Patients with diabetes have a high risk of incurring other pathologies, which can considerably shorten life expectancy ,24. AltePerinatal cells offer a wise solution as a candidate cell source for cell therapy against T1DM . In partAs a first step in creating co-cultures, we combined AEC and WJ-MSC cultures in different ratios. By using a ratio enabling a double quantity of AECs in comparison to the WJ-MSCs, co-cultures did not efficiently form spheroid-like shapes. Among the tested ratios, the most suitable and consistent cell aggregation was found in the one-to-one ratio. Co-culture in a one-to-one ratio appeared to store all cell types and have a consistent and reproducible shape and dimensions among donors and repeated experiments. Moreover, the diameter of co-culture spheroids, which is about 400 µm at the end of its formation (4 days) b, does nLaminin is a protein occurring in the basal membrane, which is a lining structure of the ECM at the interface between the epithelium and the stromal compartment of several organs . LamininAn important consideration is that spheroids derived from perinatal isolated cells, unlike organoids derived from insulin-producing cells or tissues, do not possess self-renewal capacity. A prolonged time in culture can be detrimental to cell viability. For this reason, is fundamental to also consider culture duration ahead of starting the differentiation protocol. Long-term cultured spheroids suffer metabolites and gas exchange, similar to tumorspheres; the hypoxic level can increase with negative consequences and apoptotic/necrotic cores can form in the inner part of the cell aggregates. Overall, our co-culture characterization indicates short-term cultured spheroids including AECs and WJ-MSCs are superior to long-term cultured spheroids, at least for our static culture conditions. Hyperoxia, often characterizing in vitro manipulation conditions, may cause oxidative stress by the generation of reactive oxygen species that will affect the functionality of cultured stem cells. On the contrary, a controlled level of hypoxia is a physiological stimulus characterizing many stem cell niches, including the MSC one . HyperoxIn the future, our designed co-cultures can be optimized for dynamic culturing with bioreactors , in an eAnother limitation of a co-culture is the difficulty to dissociate the spheroids to perform subsequent analyses of the single-cell type. Preliminary experiments of dissociation through enzymatic and mechanical separation were unsuccessful. A very low yield in terms of cell number and low viability levels was recovered, in particular, after the onset of intercellular junctions at both homo- and hetero-typic levels, and following the formation of strong attachment to the ECM. Moreover, any subsequent analyses of the single-cell type should require additional protocols to isolate it, creating an issue, for example, in gene expression analysis. Regarding the viability of our model, based on our results , we woulThe availability of new treatments for diabetes based on immunomodulation and differentiation strategies is currently unsatisfactory as an alternative to exogenous insulin administration. By using ethical-issue-free perinatal stem cells, we developed co-culture spheroids that resembled the epithelial-stromal organization and tissue features of pancreatic islets. The characterized spheroids can be reproducibly obtained without expensive equipment; they retained cell viability and soon matured as secretors of an ECM network. During and after short-term culture spheroids can be monitored for their biophysical characteristics, thus increasing the quality and homogeneity of the co-cultures. The possibility to employ spheroids made in a few days with an easy and cost-effective method as here reported would revolutionize the diabetes stem cell therapy approach.


Textile single-use products are dominantly used for hygiene and personal care, many of which are non-biodegradable and are frequently discarded into sewerage systems, thus causing blockages. Thus, there is a need to move towards water-soluble textiles. This research study focuses on transforming or repurposing biomass material and synthetic reusable waste plastic materials to improve waste. Chitosan (CS) nanofibers could be used in single-use nonwoven fabric or biodegradable tissues, as the water-soluble properties of chitosan nanofibers make them the perfect material for single-use applications. Furthermore, CS was blended with polyethylene terephthalate (PET) polymer and PET-based waste plastic (CS-WPET) to slow the CS nanofibers’ water degradability and strengthen the durability of the nanofiber which could be used as air filters. The CS-TFA and CS-TFA/DCM nanofiber diameters were 95.58 ± 39.28 nm or 907.94 ± 290.18 nm, respectively, as measured from the HRSEM images. The CS-PET and CS-WPET hybrid nanofibers had fiber diameters of 246.13 ± 96.36 or 58.99 ± 20.40 nm, respectively. The thermal durability of the nanofibers was tested by TGA, which showed that CS-TFA/DCM nanofibers had sufficient thermal stability up to 150 °C, making them suitable for filter or fabric use at moderate temperatures. The blended nanofibers (CS-PET and CS-WPET) were thermally stable up to 160 °C. In the aqueous medium stability test, CS-PET and CS-WPET hybrid nanofibers had a slower degradation rate and were easily dissolved, while the CS nanofibers were rapidly and completely dissolved in an aqueous medium. Blending waste PET with CS allows it to be recycled into a useful single-use, non-woven textile, with greater water solubility than unmodified PET nanofibers but more durability than CS nanofibers on their own. A large proportion of non-degradable plastic waste in the marine environment is the result of single-use synthetic plastics and discarded items . PlasticThe chitosan (CS) medium molecular weight, polyethylene terephthalate (PET), trifluoroacetic acid (TFA), and dichloromethane (DCM) were purchased from Sigma-Aldrich  and were used with no further treatment. The waste PET bottles were collected in the Cape Town municipality.The electrospinning method of chitosan was adapted from the previously conducted studies with minor modifications ,12. The The PET and WPET solutions were prepared following the same procedures described by Totito et al. (2021) . PET polThe CS-PET and CS-WPET hybrid nanofibers were produced via an electrospinning process. The volume mixing ratios of the two polymers were optimized in TFA solvent for the electrospinning process. The hybrid polymer solution ratios were prepared by mixing a certain volume of 7 wt% CS and 10 wt% PET or 10 wt% WPET solutions. Amongst the mixing volumes ratios, only a 1:1 ratio was electrospinnable. The volume ratio 1:1 was mixed at room temperature to form a homogeneous hybrid solution. Each polymer solution was electrospun following the same procedure as mentioned in 3. Then, 0.01 g of the PET and WPET nanofibers were weighed out. The nanofibers were immersed into the pH-adjusted deionized water and shaken at 190 rpm for 24 h. The nanofibers were then washed with deionized water and air-dried overnight at room temperature. The dried nanofibers were weighed thereafter to check the water stability of the nanofibers. The CS-TFA/DCM, CS-PET, and CS-WPET nanofibers were stabilized in various reagents to alter the diffusivity resistance towards aqueous mediums and decrease CS water absorption capacity. The CS-TFA/DCM, CS-PET, and CS-WPET nanofibers (0.01 g) were immersed in either 10 mL of 3 M of NaOH solution in methanol, 10 mL of saturated K2CO3 solution for 120 min, or neat ethanol solvent for 120 min; thereafter, the neutralized nanofibers were individually rapidly washed with deionized water, dried at room temperature, weighed and characterized by HRSEM.The PET and WPET nanofibers solubility test was carried out by adjusting the pH of deionized water to 1, 3, 5, 7, 9, or 11 with 0.1 M NaOH or 0.1 M HNO−1 to 650 cm−1 against transmittance with 2.0 resolutions at 64 scanning times. For every analysis, the baseline of the FTIR was corrected using the background spectrum of the blank scan. The FTIR diamond crystal and ATR holder were cleaned with ethanol before every analysis to prevent cross-contamination of the samples. The application of FTIR spectroscopy in analyzing the surface of the material involves the determination of the functional groups and chemical structures of various materials. Generally, infrared spectroscopy provides relevant information on short- and long-range coupling orders caused by other factors such as lattice bonding, electrostatics, and deterioration of the original material structure ..19]. TheThe 1:1 TFA solvent ratio CS-PET and CS-WPET hybrid nanofibers were characterized with the HRSEM to understand the morphology of the electrospun nanofibers. The HRSEM images of the 1:1 CS-PET and CS-WPET hybrid nanofiber blends show consistent, smooth, homogeneous nanofibers with an average diameter of 246.13 ± 96.36 nm for CS-PET hybrid nanofibers and 58.99 ± 20.40 nm diameter for CS-WPET hybrid nanofibers. The significant reduction in the CS-WPET nanofiber diameter size compared to the CS-PET and non-blended CS and WPET nanofibers see a,d is du−1. The stretching vibrations at 1671 cm−1 correspond to their carbonyl (C = O) functional group. The C = O represents the acetyl groups that were directly related to the backbone conformation of the chitosan [−1 band are ascribed to the combination of N-H bending, C-N, and C-C stretching vibrations [−1 corresponds to N-H deformation and C-N stretching vibration. The band at 1068 cm−1 confirms the C-O functional group [−1, 1651 cm−1, and 1417 cm−1 of the commercial chitosan used in the study reported by Kumirska et al. (2010); thus, the chitosan nanofibers were structurally similar to chitosan [In the ATR-FTIR results a, the dichitosan . The vibbrations . The waval group ,24. The chitosan ,26, not Thermogravimetric analysis of CS-TFA/DCM nanofibers is demonstrated in 2 and yielded similar outcomes as this research. El-Hefian et al. [The high thermal stability of the CS-TFA/DCM nanofibers agrees with the thermal degradation of chitosan experiments reported by de Britto et al. . CS-TFA/n et al.  also inv−1 that corresponds to the asymmetric stretching mode of the C-H bond [−1. The asymmetric C-C-O is present at 1260 cm−1 and the O-C-C stretching at the 1100 cm−1 band. The strong peak at 700 cm−1 represents the shifted aromatic functional group C-H wag, which has been affected by the presence of the carbonyl functional group [2 flow rate of 20 mL/min started with an 8.12% gradual increase in weight from 15 °C to ~380 °C. The 8.12% weight increase in the PET nanofibers is related to the expansion of the PET nanofibers, which is due to an endothermic reaction occurring. The successive thermal degradation of the PET nanofibers begins at ~380 °C and ends at ~450 °C, where a significant 70.40% weight of the PET nanofibers was lost. The depolymerization of the PET nanofibers was occurring at this second stage and formed a carbon black residue [The PET and WPET nanofibers were further characterized using the ATR-FTIR to understand the functional groups of the nanofibers as shown in C-H bond . The caral group . Thermog residue . The las residue .The first stage of the thermal decomposition for the WPET nanofibers started at about 290 °C to ~350 °C, which may be the result of the evaporation of volatile oligomers in the WPET nanofibers’ matrix. The WPET nanofibers lost about 4.55% of their weight in the first stage. Then, the weight of the WPET nanofibers was constant until degradation occurred from 400 °C to ~460 °C. At this stage, the WPET weight loss was about 72.96%. This significant weight loss was the contribution of WPET oligomers’ migration and the degradation of the ester group chain C-C-O together with the unsaturated chain of the carbonyl functional group . This waThe shape of the TGA profiles of PET and WPET nanofibers was found consistent with the increase in temperature. The first derivative plots corresponding with the TGA plots of the PET and WPET nanofibers pyrolysis at about 380 °C to ~460 °C are shown with the endothermic peak degradation in the first derivative plot at exactly 402 °C or 430.60 °C, respectively. Finally, the PET and WPET nanofibers’ thermal decomposition ended when the reaction ceased at a residue accumulation of ~9%. This corresponds with the thermal degradation investigation of waste polyethylene terephthalate (PET) under inert and oxidative environments studied by Das and Tiwari .−1 and 2964 cm−1 that corresponds to the C-H stretching and the combination of the carboxylic acid COOH and amino acids NH2 that indicates the presence of the PET or WPET in the nanofibers. The medium bands at 1792 cm−1 and 1718 cm−1 correspond to the C = O vibrations of the acetyl ester functional group also present in the PET and WPET structural formula. The medium band at 1020 cm−1 corresponds to the O bridge stretching in the chitosan structural formula. Asymmetrical C-H bending of the CH2 functional group is present at 1371 cm−1 and 1267 cm−1 bands, which also proves the presence of the CS molecules [The CS-PET and CS-WPET nanofibers were characterized using the ATR-FTIR technique to identify the functional groups of the 1:1 CS-PET and CS-WPET nanofibers e. The FTolecules .Thermogravimetric (TGA) analysis of 1:1 CS-PET and CS-WPET hybrid nanofibers is presented in PET, WPET, CS-TFA/DCM, CS-PET, and CS-WPET electrospun nanofibers were studied for pH stability and solubility behavior, and the recoverable materials were characterized using HRSEM and ATR-FTIR techniques. The electrospun nanofibers were tested at different pHs for the mass difference that may occur upon exposure to the solution. This will give an insight into each polymer nanofiber’s performance in acidic, basic, or neutral mediums. This stability test showed the pH-related degradation behavior of PET and WPET nanofibers, respectively .In The CS-TFA and CS-TFA/DCM nanofibers were completely soluble in all pH-adjusted aqueous solutions and thus would be immediately degraded in water when discarded after use. The CS-TFA/DCM nanofibers were stabilized to increase the diffusivity resistance in aqueous mediums and decrease its water solubility compared to CS-TFA nanofibers. The CS-TFA/DCM nanofibers were therefore stabilized by neutralization to check if the CS-TFA/DCM nanofibers could be stable in a wet wipes solution for single-use personal hygiene care. The CS-TFA/DCM nanofibers (0.01 g) were immersed in10 mL of 3 M of NaOH solution in methanol;2CO3 solution and ethanol solvent for 120 min.K2CO3 previously reported by Haider and Park [2O. Therefore, CS-TFA/DCM nanofibers stabilized with 3 M of NaOH solution in methanol, resulting in nanofibers with stable residues remaining. Further characterization was carried out on CS-TFA/DCM nanofibers stabilized with 3 M of NaOH solution in methanol.Thereafter, the neutralized CS-TFA/DCM nanofibers were individually rapidly washed with deionized water. The CS-TFA/DCM nanofibers that had been stabilized in Kand Park  completeand Park . Both ofThe HRSEM image shows that the CS-TFA/DCM nanofibers stabilized with 3 M NaOH in methanol lost their fibrous character after the stabilization protocol a. The CS−1 corresponds to the combination of the OH and NH functional groups, which were also present in the chitosan [−1 corresponds to the ammonium ions that may have remained after the stabilization. The weak band at 1650 cm−1 corresponds to the aromatics and amine functional groups of chitosan. The bending vibrations at 1410 cm−1 were assigned to the carboxyl functional group of chitosan. The band at 1025 cm−1 confirmed the presence of C-O functional groups of chitosan [The functional groups of the stabilized chitosan nanofibers are shown in the FTIR spectrum b above. chitosan ,42. The chitosan ,43. Thus−1 that corresponded to the C-H stretching and the combination of the carboxylic acid COOH and amino acids NH2 that represented the presence of the PET and WPET in the nanofibers. The medium bands at 1640 cm−1 and 1563 cm−1 corresponded to the C = O vibrations of the acetyl ester functional group also present in the PET and WPET structural formula. The medium band at 1023 cm−1 corresponded to the O bridge stretching in the chitosan structural formula, thus showing that traces of CS remained after treatment. Asymmetrical C-H bending of the CH2 functional group was present at the 1411 cm−1 band, which also proved the residual presence of the chitosan molecules [The HRSEM images a of CS-Polecules ,38. FromThe alarming amount of non-degradable single-use synthetic plastic waste found particularly in the marine environment has motivated scientists to implement new strategies for designing and synthesizing single-use biodegradable fabrics or textiles and reusing plastic waste. Chitosan, being the deacetylated polymer from waste shellfish, scales of fish, and insects, was electrospun into CS-TFA/DCM nanofibers using 0.1 mL/hr, 25 kV, and 14 cm conditions. The best solvent for electrospinning a chitosan polymer was found to be a mixture of trifluoroacetic acid and dichloromethane in 7:3 ratios with 7 wt% of CS-TFA/DCM. CS-TFA/DCM resulted in bead-free nanofiber morphology compared to CS-TFA. The thermal decomposition ranges of CS-TFA/DCM nanofibers started at lower temperatures than CS-PET and CS-WPET nanofibers, but CS-TFA/DCM nanofibers had sufficient stability up to 200 °C, which makes them sufficiently durable at moderate temperatures in dry environments. The blended nanofibers (CS-PET and CS-WPET) were electrospun using the TFA solvent, forming hybrid nanofibers that were thermally stable up to 160 °C, with a slower degradation rate and easily soluble in an aqueous medium. While the CS nanofibers completely dissolve in an aqueous medium, blending waste PET with CS allows it to be recycled into a useful non-woven textile with greater water solubility than unmodified PET nanofibers but more durability than CS nanofibers on their own. Stabilization with 3 M NaOH in methanol did not result in a beneficial outcome, as this procedure resulted in deformed nanofibers. CS nanofibers can be used as dry, single-use, nonwoven fabric for air filters, masks, or personal hygiene in medical applications, as the morphology of the nanofiber non-woven fabric presents fine interfiber pores suitable for trapping viruses and bacteria. If used for infection control, these contaminated fabrics could be thermally combusted through depolymerization in a furnace, forming carbon residue. PET and WPET were robust, and when blended with CS their biodegradability properties were enhanced, also affording possible application as a dry air filter or wipe, as they could be discarded after use without concern as the composite fabric would degrade much more rapidly than PET in the environment. The CS-TFA/DCM nanofibers are much more easily discarded, as these nanofibers will completely decompose and dissolve in water with no waste buildup in the environment. Therefore, CS-TFA/DCM nanofibers can be used for single-use personal hygiene care as a highly water soluble, dry nonwoven textile to replace synthetic polymer nanofibers. For water-durable fabric, the CS-WPET nanofibers made using chitosan and waste plastic bottles , offered a product that reuses waste and may have an extended utility before it degrades. The CS-WPET hybrid nanofibers were reported on for the first time in this research. For future work, it is recommended that upscaling of the chitosan and composite nanofibers is performed to replace personal hygiene single-use materials, minimize plastic pollution, and minimize marine and land pollution. This study also recommends that further studies be carried out on the intermediate stabilization of the nanofibers. It is recommended that before use, the CS-WPET nanofiber fabrics to be implemented for hygiene care undergo quality assurance and be tested according to ISO 9001, ISO 179, ISO 22716, and ISO/TC 217.


TGM2, TMEM51, TAC3, NDRG4, and PDGFB as more connected in the NP heifers’ network. The NP gene network showed a connectivity gain due to the rewiring of major regulators. The metabolomic analysis identified 18 and 15 hub metabolites in the AI-P and NP networks. Tryptophan and allantoic acid exhibited a connectivity gain in the NP and AI-P networks, respectively. The gene–metabolite integration identified tocopherol-a as positively correlated with ENSBTAG00000009943 in the AI-P group. Conversely, tocopherol-a was negatively correlated in the NP group with EXOSC2, TRNAUIAP, and SNX12. In the NP group, α-ketoglutarate-SMG8 and putrescine-HSD17B13 were positively correlated, whereas a-ketoglutarate-ALAS2 and tryptophan-MTMR1 were negatively correlated. These multiple interactions identified novel targets and pathways underlying fertility in bovines.Reproductive failure remains a significant challenge to the beef industry. The omics technologies have provided opportunities to improve reproductive efficiency. We used a multistaged analysis from blood profiles to integrate metabolome (plasma) and transcriptome  in beef heifers. We used untargeted metabolomics and RNA-Seq paired data from six AI-pregnant (AI-P) and six nonpregnant (NP) Angus-Simmental crossbred heifers at artificial insemination (AI). Based on network co-expression analysis, we identified 17 and 37 hub genes in the AI-P and NP groups, respectively. Further, we identified  Infertility has a negative impact on beef cattle production and the profit of the livestock industry. Despite technological advancements and improvements in management practices , reproduPredominantly, producers have used traits, such as body condition score ,6,7, repRPL39, SMIM26, N6AMT1, LONRF3, and GATA3 as differentially expressed in peripheral white blood cells associated with pregnancy outcomes in beef heifers [IGF1, AGT, TNF, PI3K, FGF2, TGF-β1, and related biological mechanisms important for pregnancy establishment in endometrial transcriptome [IGJ, IGLL1-2, CLCA1, PLA2G2F, and SHISA6 as differentially expressed in the endometrial biopsies of subfertile and fertile heifers [A plethora of transcriptomic studies from embryo ,15, endo heifers . Mazzonicriptome . Similar heifers . Likewis heifers ,26,27 an heifers ,29 shed  heifers . DespiteWhile the abovementioned studies provide insights into the molecular basis of fertility, to the best of our knowledge, there is a paucity of information about the integrated relationship between fertility, gene expression, and metabolite abundance. We hypothesized that fertility potential is partially determined by the co-expression of genes and metabolites and their coordinated interaction. Thus, our main objective was to unravel the transcriptomic and metabolomic architecture and the biological pathways underlying heifer fertility. To accomplish this, we integrated peripheral white blood cells transcriptome and plasma metabolome profiles using a network approach to unveil functional candidate genes and metabolites involved with heifer fertility. Additionally, we shed light on fertility-related pathways derived from the gene–metabolite pairs.We used the RNA-Seq expression profile from peripheral white blood cells and the plasma metabolome to ascertain the putative mechanisms underlying fertility differences between AI-P and NP; six animals were in each group of beef heifers. A schematic representation of the study design and analysis steps is given in p-value ≤ 0.05 and absolute (log2 fold change ≥ 0.5))  included SAXO2, ENSBTAG00000039555, ENSBTAG00000034871, ART3, and ENSBTAG00000048169.After quality control see , we main ≥ 0.5)) . Among tTo identify genes or metabolites with coordinated expression patterns within the AI-P and NP groups, we used a co-expression network approach based on the partial correlation and information theory (PCIT) algorithm . For eacp-value ≤ 0.05) and co-expressed with the DEGs  and 1164 edges (interactions) a. The nop-value ≤ 0.05). The NP group was used as the reference to determine the gain or loss in gene connectivity . Similarly, 6670 metabolite pairs were identified in the NP group. Previously, Phillips et al. reported fifteen differentially expressed metabolites (DEMs) [p-value ≤ 0.05). Considering this approach, 18 and 15 metabolite pairs for the AI-P and NP groups (corresponding to 23 unique metabolites in each) were maintained for further analysis  . We thenanalysis .Based on the degree and betweenness centrality topological parameters calculated by NetworkAnalyzer, we found eight and four hub metabolites for the AI-P and NP networks, respectively . Ornithip-value ≤ 0.05). The gain or loss connectivity was calculated based on the NP group . Based on that, we identified 1161 gene–metabolite pairs in the AI-P network and 155 in the NP networks  (To retrieve the gene–metabolite pairs based on the Integration of Linear model (IntLIM) approach, we utilized 1098 genes and 40 metabolites that were differentially expressed (DEGs and DEMs) or targets  for the AI-P and NP groups. After filtering for 5% variation, 1043 genes and 40 metabolites were maintained for data integration. This analysis resulted in 3177 gene–metabolite pairs ( ≤ 0.05) . Next, w ≤ 0.05)  by filteEXOSC2, TRNAUIAP and SNX12. In the NP group, the α-ketoglutarate-SMG8 and putrescine-HSD17B13 pairs were positively correlated, whereas α-ketoglutarate-ALAS2 and tryptophan-MTMR1 were negatively correlated.Lastly, we overlapped the results from the PCIT and IntLIM to explore those gene–metabolite pairs that were identified in both approaches. These pairs included tocopherol-α, which was positively correlated in the AI-P group with ENSBTAG00000009943 and negatively correlated in the NP group with Currently, beef heifers are selected based on phenotypic assessments. However, a proportion of heifers that pass phenotypically remain NP after the breeding season. Understanding the genetic basis involved in complex traits, such as fertility, will be advantageous in efficiently selecting beef heifers and benefit cow-calf production. The phenotypic outcome of genomic and transcriptomic influences on the molecular state of the cell is reflected by the metabolome . TherefoTo systematically identify all molecules and their interactions exhibited in the blood for fertility, we used the gene and metabolite co-expression network approach. This approach identified the correlations and recognized the genes and metabolites playing a role in fertility. To accomplish this, we first identified the DEGs and retrieved the DEMs from our previous study . Next, wTAC3 (tachykinin precursor 3) was identified as upregulated and a hub with a network connectivity gain in the NP group. The TAC3 gene encodes a neuropeptide essential to regulating human reproductive function. Supporting human reproductive biology, TAC3 has been identified in the bloodstream of patients with central pubertal disorders and hypogonadotropic hypogonadism [TAC3 modulates gonadotropin-releasing hormone (GnRH), which is responsible for the secretion of follicle-stimulating hormone (FSH) and luteinizing hormone (LH) [TAC3 requires the presence of sex steroids to increase FSH and LH secretion [TAC3 identified in blood, and yet the heifers not becoming pregnant may suggest an alteration in the hormonal and sex-steroid levels. FSH and LH signaling also regulate several pathways in ovarian granulosa cells, such as the mitogen-activated protein kinase (MAPK) pathway [PDGFB (platelet-derived growth factor) as significantly upregulated and differentially connected with a connectivity gain in the NP group. PDGFB, identified as a constituent of blood serum and platelets [PDGFB signaling promotes epithelial–mesenchymal transition (EMT), which is essential for embryogenesis [PDGFB is negatively and differentially correlated with the hydrocinnamic acid in the NP group. Hydrocinnamic acid is an important class of phenolic acid, having antioxidant and anti-inflammatory properties [PDGFB gene and the downregulation of hydrocinnamic acid in the NP group triggered the MAPK signaling pathway, likely regulating the inflammatory response. Controlled inflammation is necessary for host defense, while an uncontrolled inflammatory response may affect fertility [PDGFB and hydrocinnamic acid in reproductive cells or tissue types could highlight precise downstream mechanisms underlying fertility.We identified 38 DEGs and 15 DEMs from blood plasma between the AI-P and NP beef heifers. Among the DEGs, gonadism . The proone (LH) . Howeverecretion . Thus, t pathway . The MAP pathway . In our latelets , modulatlatelets , which ilatelets ,46. Studogenesis . EMT regogenesis . The MAPogenesis . Furtherogenesis . In our operties . Phenolioperties . A previoperties . Therefoertility . HoweverANAPC13, CAMK2G, CCNE2, PPP2R1B, PPP2R5A and PPP3CA. The CAMK2G gene encodes a calcium/calmodulin-dependent protein kinase involved with GnRH release [CAMK2G was positively correlated with TGM2 (Transglutaminase 2) as given through PCIT in our study. TGM2 was upregulated and identified as a hub in the NP group. This result was further supported as TGM2 was significantly upregulated in uterine fluid collected from infertile women [TGM2 levels were higher in the blood of patients with endometrial cancer [TGM2 activates the β-catenin (Wnt) pathway, which impairs ovulation [We identified the over-represented oocyte meiosis and Wnt signaling pathways in the AI-P group. The genes included  release . CAMK2G le women . Furtherl cancer . TGM2 acvulation . Balancevulation . A previvulation . AlthougNDRG4 (N-Myc downstream-regulated gene 4), downregulated in the AI-P group. NDRG4 has a crucial role in transferring its repression effect on PI3-Akt activity [NDRG4 activation and consequent PI3-Akt suppression [NDRG4 was identified as a hub with a network connectivity gain in the NP group. Previous studies reported the NDRG4 expression in other reproductive tissue types [NDRG4 has a potential role in regulating fertility and could be further explored.The PI3-Akt signaling pathway was over-represented by significant gene–metabolite pairs in the AI-P group. PI3-Akt signaling pathway plays an essential role in cell proliferation, apoptosis, metabolism, regulation of dormancy, and activation of mammalian primordial follicles . Decreasactivity . Studiespression , which cue types , but itsGRB10 (growth factor receptor bound protein 10) that was upregulated and differentially connected (loss in connectivity) in the NP group. GRB10 interacts negatively with insulin and insulin-like growth factor receptors [GRB10 gene during oocyte maturation in the bovine cumulus–oocyte complex [GRB10 with superovulation traits in cattle suggested the recovery of many embryos from heterozygous GRB10 cattle [GRB10 in regulating fertility, but a comprehensive understanding of bovine fertility requires further investigation.Insulin-like growth factors modulate pathways, such as MAPK and PI3-Akt, by regulating gamete development, quality, and implantation . Our stueceptors ,67,68. P complex . The ass0 cattle . These sART3, MTMR1, ALAS2, TFF2, SMG8, PLEKHF1 and EXOSC2 as unique hub genes in the NP group. ART3 (ADP-Ribosyltransferase-3) was downregulated and positively correlated with ornithine, putrescine and alpha-ketoglutarate in the NP group. As a representative arginine-specific ART-ribosyltransferase, ART3 has been reported to play a critical role in cell division, DNA repair, and inflammatory response [ART3 and its correlated metabolites (ornithine and putrescine) in the NP group.The network analysis identified response . Argininresponse . In prevresponse . Interesresponse . These fMTMR1 (myotubularin-related protein 1), a hub gene in the NP network. Tryptophan levels are influenced by dietary and hormonal factors [Tryptophan was identified as differentially connected with a connectivity gain in the NP group. Tryptophan was negatively correlated with  factors . Free tr factors . The pre factors . The nee factors . Further factors . Additio factors . This ev factors .The genes, metabolites, and their interactions identified in the present study over-represented some pathways playing a role in fertility. Some of the genes and metabolites were supported by the previous literature; however, some other targets identified were novel and warrant further detailed studies to evaluate the repeatability of our results in a larger cohort. As the heifers undergo variations during the estrus cycle and pregnancy, it is obvious to expect alterations in genes and metabolite profiles at a particular time point. This means that strategies for applying this information in real-time farming appear to be more complex and need a better understanding of the changes in genes, metabolites, and their interactions at different time points. Validation of these results in more samples and different time points would help to establish a framework for future fertility prediction using gene and metabolite biomarker profiles that could be practical for on-farm use and improve reproductive efficiency. Furthermore, validation of these genes and metabolites in the reproductive tissues and cells would help to identify the therapeutic targets for fertility.The RNA-Seq and metabolomic datasets previously generated by our group and publicly available were used in the current study. The experimental design, sample collection, and data generation were published elsewhere ,25. BrieRaw gene counts of 12 samples classified as AI-P or NP with six animals in each group from “station B” were downloaded from the GEO database (accession number GSE103628) . RNA-SeqPrior to statistical analysis, the read count data were transformed to counts per million (CPM) using edgeR v3.28.1 . For thep-value ≤ 0.05 and absolute (log2 fold change) ≥ 0.5 were considered significant. The NP heifers were used as the reference group, and DEGs were classified as up- or downregulated based on the log2 fold change direction. The upregulated and downregulated genes were visualized using a volcano plot constructed using the R-package EnhancedVolcano v1.8.0 [We used the following two methods for the differential expression analysis: edgeR and DESeq2. This was performed to increase the robustness of our analysis and capture the biological variation. Thus, DEGs identified by both tools with a o v1.8.0 . The folFor metabolomics, raw data files were preprocessed and quantification was reported as peak height using unique ion as default . For eacnormTransform function from DESeq2, read counts were normalized and used as input for PCIT analysis. For the metabolite networks, 122 metabolites were used after data normalization  approach was used to identify expression patterns and relationships within each regulatory layer (transcriptome and metabolome). PCIT reports the significantly correlated pairs after comparing all possible trios of genes or metabolites . Gene cop-value ≤ 0.05) were determined based on partial correlation values greater than absolute (r ≥ 0.99) and absolute (r ≥ 0.9) for genes and metabolites, respectively. Additionally, significant pairs were maintained when a DEG or DEM was co-expressed.Gene and metabolite networks were created separately for the AI-P and NP groups. This approach allowed us to identify changes in the network topology between conditions by comparing the connectivity of genes and metabolites. To reduce data dimensionality, a more stringent correlation value was used to select the gene pairs. Significantly correlated pairs  are central to the network architecture and may be the primary regulators of biologically meaningful pathways.Network topological parameters, including degree and betweenness centrality, were computed by the Cytoscape v3.8.2  plugin NDK) index, which is the ratio of the node (gene or metabolite) connectivity to the maximum connectivity for each group [DKi and DKi. Significantly differentially connected genes or metabolites  were retrieved when z-score values were between p-value ≤ 0.05). The networks were constructed and visualized using Cytoscape v3.8.2.To visualize changes in nodes and edge rewiring from the AI-P and NP groups, we used the Cytoscape plug-in—DyNet . DyNet pch group . The indTwo approaches were used to unravel the complex relationship between genes and metabolites within the AI-P and NP groups. First, we created a single co-expression network combining the normalized genes  and metabolites (122) on PCIT to identify significantly correlated gene–metabolite pairs . Only geunique” targets. Herein, unique targets refer to the overlapping hub and differentially connected targets between the AI-P and NP groups. The networks with significant gene–metabolite pairs for the AI-P and NP groups were visualized in Cytoscape. Likewise, nodes and edge rewiring within the interaction networks were performed using DyNet (Cytoscape v3.8.2).To get an insight into the specific networks involved with fertility status, the correlated pairs were filtered with the “m: is the log-normalized metabolite abundance;b1: is the intercept;b2g: is the normalized and adjusted gene-expression level;b3p: is the phenotype (AI-P and NP);b4 (g:p): is the interaction between gene expression and phenotype; ande: is the residual effect associated with each observation.The second approach was based on a linear model framework using the IntLIM (Integration of Linear model) R-package . IntLIM p-value ≤ 0.05). The absolute difference between the groups was estimated as (rPreg_cor—rNP_cor), where rPreg_cor and rNP_cor are the correlation values for the AI-P and NP groups.The absolute difference in the Spearman correlation was identified between the groups to identify significant gene–metabolite pairs  were considered significant.For the significant gene–metabolite pairs, joint-pathway analysis was performed using MetaboAnalyst 5.0 specific to The current study focused on identifying putative major regulators associated with fertility. To this end, we investigated the differences in the gene or metabolite expression and co-expression in beef heifers. Additionally, an integrated gene–metabolite analysis approach using correlation and linear model unveiled the potential gene–metabolite pairs affecting biological processes related to fertility in beef heifers. This research’s originality lies in multiple approaches used in determining gene–gene, metabolite–metabolite, and gene–metabolite interactions at AI. A detailed understanding of these targets and their underlying pathways in a bigger cohort at AI and at different time points could establish a framework for fertility prediction. More data and validation of these results would help model the complex relation of gene–metabolite profile over time.